• Proceedings of the KIEE Conference
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• 2001.10a
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• pp.230-232
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• 2001

The camera system we researched has two stepping motors for the pan and tilt operation, and the human face tracking algorithm. Recently, this kind of the camera is used in PC communication, telecommunication vision meeting and tele-lecture. This paper discusses the smooth speed control method of this camera when the face is moved to up, down, left and right direction. We used a mean shift algorithm for the face-tracking, proposed the speed control algorithm using a fuzzy logic and certified this characteristics with the experiment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.57-61
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• 2008

우리나라의 자동차의 수는 1990년부터 계속 증가하고 있다. 계속되는 자동차수의 증가로 인해 휴일, 출퇴근 시간에 교통이 혼잡 또는 마비되는 문제가 발생한다. 하지만 기존의 신호등 체계는 통계적인 수치에 의해 결정되기 때문에 항상 일정하지 않은 차량의 수를 제어하기에는 한계가 있다. 따라서 본 논문에서는 실시간으로 변하는 차량의 수와 점유시간에 따라 퍼지 제어 기법을 이용하여 신호를 제어하는 방법을 제안한다. 제안된 교통 신호 제어 방법은 교차로에 대기하는 차량의 수와 점유 시간을 퍼지 제어 기법에 적용하여 차량의 진행 신호에 대한 우선순위를 부여한다. 가장 높은 우선 순위를 가지는 현시에 대해 진행 신호를 부여하고 나머지는 대기하게 된다. 그리고 진행 신호의 시간을 교차로에 대기하는 모든 차량의 수와 차량의 비율, 진행 신호를 부여받은 차량의 수를 이용하여 계산한다. 본 논문에서는 제안된 펴지 신호 제어 기법과 정적인 신호 제어 기법에 대해 시뮬레이션을 통해 실험한 결과 차량 혼잡도와 상관없이 제안된 차량 신호 제어 기법이 동일한 시간에 더 많은 차량이 원활하게 소통되는 것을 확인하였다.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1034-1036
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• 1996

In this paper, an adaptive fuzzy logic controller is presented for auto-tunning of the scaling factors by using learning capability of neural networks. The proposed scheme consists of the FLC which includes the PI-type FLC and PD-type FLC in parallel form and the neural network which learns scale factors of FLC. Computer simulations were performed to illustrate the effectiveness of a proposed scheme. A proposed FLC controller was applied to the second order system and velocity control of the brushless DC motors. For the design of the FLC, tracking error, change of error, and acceleration error are selected as input variables of the FLC and three seal e factors were used in the parallel-type FLC. This scheme can be used to reduce the difficulty in the selection of the scale factors.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.293-297
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• 1996

For the representative beat calculation and efficient rhythm analysis new method, that is, QRS typification were proposed. A problem that were resulted from pattern classification based on binary logic could be solved out by the fuzzy clustering and classification nodes could be reduced by using the proposed new feature vector. The accurate representative beat could be obtained by excluding the ST-T segment that happened outlier through ST-T segment typification procedure.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.220-224
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• 2008

This paper presents the polygon-based Q-leaning and Parallel SVM algorithm for object search with multiple robots. We organized an experimental environment with one hundred mobile robots, two hundred obstacles, and ten objects. Then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning, and dodecagon-based Q-learning and parallel SVM algorithm to enhance the fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process. In this paper, the result show that dodecagon-based Q-learning and parallel SVM algorithm is better than the other algorithm to tracking for object.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.41.6-41
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• 2001

As autonomous mobile robot become more widely used in industry, the importance of navigation system is rising, But eh primary method of locomotion is with wheels, which cause man problems in controlling tracked mobile robots. In this paper, we discuss the used navigation control of tracked mobile robots with multiple sensors. The multiple sensors are composed of ultrasonic wave sensors and vision sensors. Vision sensors gauge distance using a laser and create visual images, to estimate robot position. The 80196 is used at close range and the vision board is used at long range. Data is managed in the main PC and management is distributed to ever sensor. The controller employs fuzzy logic.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.81-89
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• 2009

In this thesis we have developed an algorithm to evaluate each student's level of understanding and find out which subjects they are not good at when they get on-line lectures at a cyber university. This algorithm is based on fuzzy logic using each student's scores adjusted according to the level of difficulty. In addition, we also introduced a "duplex intellectual lecturing system" and an "evaluation method based on the level of understanding." With the duplex intellectual lecturing system students can ask questions on line at a cyber university and under the new evaluation method, there is no need for students to move between classes. As a result of a computer simulation test, the duplex on-line lecturing system has proven to be more effective than the current one-way cyber lecturing system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.281-292
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• 2016

The proposed scheme is based on the modified perturb and observe (P&O) algorithm combined with the sliding mode technique. A modified P&O algorithm based sliding mode controller is developed to study the effects of partial shade, temperature, and insolation on the performance of maximum power point tracking (MPPT) used in photovoltaic (PV) systems. Under partially shaded conditions and temperature, the energy conversion efficiency of a PV array is very low, leading to significant power losses. Consequently, increasing efficiency by means of MPPT is particularly important. Conventional techniques are easy to implement but produce oscillations at MPP. The proposed method is applied to a model to simulate the performance of the PV system for solar energy usage, which is compared to the conventional methods under non-uniform insolation improving the PV system utilization efficiency and allowing optimization of the system performance. The modified perturb and observe sliding mode controller successfully overcomes the issues presented by non-uniform conditions and tracks the global MPP. Compared to MPPT techniques, the proposed technique is more efficient; it produces less oscillation at MPP in the steady state, and provides more precise tracking.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.1
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• pp.76-82
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• 2005

Speech signal has various features of speakers. This feature is extracted from speech signal processing. The speaker is identified by the speaker identification system. In this paper, we propose the speaker identification system that uses the incremental learning based on neural network. Recorded speech signal through the microphone is blocked to the frame of 1024 speech samples. Energy is divided speech signal to voiced signal and unvoiced signal. The extracted 12 orders LPC cpestrum coefficients are used with input data for neural network. The speakers are identified with the speaker identification system using the neural network. The neural network has the structure of MLP which consists of 12 input nodes, 8 hidden nodes, and 4 output nodes. The number of output node means the identified speakers. The first output node is excited to the first speaker. Incremental learning begins when the new speaker is identified. Incremental learning is the learning algorithm that already learned weights are remembered and only the new weights that are created as adding new speaker are trained. It is learning algorithm that overcomes the fault of neural network. The neural network repeats the learning when the new speaker is entered to it. The architecture of neural network is extended with the number of speakers. Therefore, this system can learn without the restricted number of speakers.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.13-18
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• 2007

Human's sight holds the most extents for recognizing information among other senses. If we make much better visualized environment for human, it will become more beneficial in person's emotion or body. Human is using a lot of display units in modern society. Basic hues ate Red, Green and Blue. Using these three colors, we can change hue sense and degree of brightness of display unit. If we control hue of unit to be suitable according to individual environment, we can feel comfortable or reduce stress. In this paper, we present Human-Friendly Intelligent Hue Control System(HFIHCS) that control hue of display unit using fuzzified factors related to human's emotion and environment. The effectiveness of the proposed system is demonstrated by questionnaire.